On on-going discussion in Linkedin and other forums (or should that be ‘fora’?) is the difference between ‘Enterprise Architecture’ and ‘Business Architecture’. In a rational world they would both be seen as the same thing. However, not all people who get involved in the ‘architecture’ worlds are rational! Words Matter The reason this discussion arises [...]
Address Universal Modelling Tool
Address Modelling Magic The different structures of addresses in different countries and different languages can seem to be an insurmountable obstacle when trying to bring consistency of address structures for the purposes of Data Quality and Master Data Management. Without the right tool it is insurmountable. However, with the right tool is becomes relatively simple. [...]
The Phantom Entities of Customer and Supplier
It is amazing how much is spoken and written about Customer and Supplier, especially as they do not exist – they are Phantom Entities! Read more at There’s No Such Thing as Customer.
Recently, in a response to a comment on The Pathology of Business & Data Modelling I was addressing this topic once again and thought it would be useful to produce some models that show how Customer and Supplier are in fact Roles played by the entity Party.
If I Wanted to Get to Dublin I Wouldn’t Start from Here: Part 1
It seems that most Master Data Management (MDM) projects are starting in the wrong place and heading in the wrong direction! They fail to build and use that essential and most powerful of MDM tools, the Logical Data Model (LDM).
This approach is about as productive and effective as building a ship without a keel!
This is the first of three posts that explain what the problems are and how top avoid them.
Data Quality – One Version of the Truth?
The concept of “one version of the truth” is possibly the most widely discussed (and disputed) topics in Data Quality. Some say that it can never exist, others, that it must always exist or there is no quality. There is one version of the truth but, perhaps, not the truth as you know it! Know the Unique Identifier (UID) and the truth becomes blindingly obvious!
Click on “Read More” to see how.
There Are No Such Things as Data Rules!
This may come as a surprise to many involved in Data Quality but, wait for it, there are no such things as data rules! By looking at data you can never deduce or define a rule that dictates that one entity should be related to another or that a value of an attribute of an entity has to be, in a certain format and have limits to its value. So what does dictate data content, structure, format and constraints?
Click on “Read More” and find out why….
There's No Such Thing as a Customer!
“Customer” is one of the Data Enitities that lies at the heart of most MDM practices in enterprises around the world and it is not in fact a Data Entity at all! This situation has arisen because far too much “data quality” work is done without the use of a properly structured Logical Data Model. This work then serves to perpetuate rather than remove fragmented data structures.
Business Modelling Architecture
All good analysis and modelling is achieved by starting in the right place, and that place is with the core activities of the enterprise – the Business Functions. If you have not started in the right place, then you need to know how to get back there. The Hierarchy of Models shown in the diagram in this post will enable you to do this.
If you are working on any model and have not built the preceding model(s) then you are not going to achieve a Quality outcome. For example, if you are modelling Processes and have not yet built your Function Model, then you are in trouble. This failure to first model Functions is one of the main reasons why most BPM projects fail to deliver.
A Data Quality Profession?
Do We Need a Data Quality Profession? In a recent article on Data Quality Arkady Maydanchik was suggesting that a key solution to the current data quality issues that plague business everywhere is the creation of a dedicated Data Quality profession. In a reply to the article I suggested that, far from solving the problems, the [...]
Bad Data Structures Prevent Growth
Postal addresses present data database developers with a constant challenge. Traditional approaches fail, either because they hard code in inadequate structures, or they provide the chaos of no structure at all. Generic data modeling can overcome both of these shortcomings and enable to expand and grow into multinational markets.
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